IRSOM2: a web server for predicting bifunctional RNAs.

Recent advances have shown that some biologically active non-coding RNAs (ncRNAs) are actually translated into polypeptides that have a physiological function as well. This paradigm shift requires adapted computational methods to predict this new class of 'bifunctional RNAs'. Previously, we developed IRSOM, an open-source algorithm to classify non-coding and coding RNAs. Here, we use the binary statistical model of IRSOM as a ternary classifier, called IRSOM2, to identify bifunctional RNAs as a rejection of the two other classes. We present its easy-to-use web interface, which allows users to perform predictions on large datasets of RNA sequences in a short time, to re-train the model with their own data, and to visualize and analyze the classification results thanks to the implementation of self-organizing maps (SOM). We also propose a new benchmark of experimentally validated RNAs that play both protein-coding and non-coding roles, in different organisms. Thus, IRSOM2 showed promising performance in detecting these bifunctional transcripts among ncRNAs of different types, such as circRNAs and lncRNAs (in particular those of shorter lengths). The web server is freely available on the EvryRNA platform: https://evryrna.ibisc.univ-evry.fr.

SBSA: an online service for somatic binding sequence annotation.

Efficient annotation of alterations in binding sequences of molecular regulators can help identify novel candidates for mechanisms study and offer original therapeutic hypotheses. In this work, we developed Somatic Binding Sequence Annotator (SBSA) as a full-capacity online tool to annotate altered binding motifs/sequences, addressing diverse types of genomic variants and molecular regulators. The genomic variants can be somatic mutation, single nucleotide polymorphism, RNA editing, etc. The binding motifs/sequences involve transcription factors (TFs), RNA-binding proteins, miRNA seeds, miRNA-mRNA 3'-UTR binding target, or can be any custom motifs/sequences. Compared to similar tools, SBSA is the first to support miRNA seeds and miRNA-mRNA 3'-UTR binding target, and it unprecedentedly implements a personalized genome approach that accommodates joint adjacent variants. SBSA is empowered to support an indefinite species, including preloaded reference genomes for SARS-Cov-2 and 25 other common organisms. We demonstrated SBSA by annotating multi-omics data from over 30,890 human subjects. Of the millions of somatic binding sequences identified, many are with known severe biological repercussions, such as the somatic mutation in TERT promoter region which causes a gained binding sequence for E26 transformation-specific factor (ETS1). We further validated the function of this TERT mutation using experimental data in cancer cells. Availability:http://innovebioinfo.com/Annotation/SBSA/SBSA.php.

sideRETRO: uma ferramenta de bioinformática dedicada à identificação deinserções polimórficas, germinativas ou somáticas, de pseudogenes processados / sideRETRO: a bioinformatics tool for identifying somatic and polymorphic insertions of processed pseudogenes

Os avanços metodológicos e instrumentais decorrentes do Projeto Genoma Humano formaram o arcabouço necessário para o surgimento das tecnologias de sequenciamento de DNA de Nova Geração, as quais se caracterizam por um custo reduzido, uma baixa demanda operacional e a produção de um grande volume de dados por experimento. Concomitantemente a isso, o aumento no poder de processamento computacional permitiu o desenvolvimento de análises genéticas em larga escala, de modo que, atualmente, é possível estudar características genômicas individualizadas e, até então, pouco ou nunca exploradas. Dentre essas características, aquelas relacionadas às variações estruturais em genomas têm recebido bastante atenção. Os pseudogenes processados, ou retrocópias, são variações estruturais causadas pela duplicação de genes codificadores mediante à transposição de seu RNA mensageiro maduro pela maquinaria enzimática de LINE- 1. As retrocópias podem estar fixadas, ou seja, presentes em todos os genomas de uma dada espécie, os quais são representados pela montagem modelo do genoma de referência, ou podem não estar fixadas, sendo polimórficas, germinativas ou somáticas. No entanto, o conhecimento acerca das retrocópias não fixadas ainda é limitado devido à falta de ferramentas de bioinformática dedicadas a sua identificação e anotação em dados de sequenciamento de DNA. Posto isso, este trabalho apresenta o sideRETRO um programa computacional especializado na detecção de pseudogenes processados ausentes do genoma de referência, mas presentes em dados de sequenciamento de genoma completo e exoma de outros indivíduos. Além de apontar para a presença de retrocópias não fixadas, o sideRETRO é capaz de anotar várias outras características relacionadas a esses evento, tais como: a coordenada genômica de inserção do pseudogene processado, a qual constitui o cromossomo, o ponto de inserção e a fita de DNA (líder or retardada); o contexto genômico do evento (exônico, intrônico ou intergênico); a genotipagem (presente ou ausente) e a haplotipagem (em homozigose ou heterozigose). Para atestar a eficiência da ferramenta, o sideRETRO foi executado para dados simulados e para dados reais validados experimentalmente por um grupo independente. Portanto, em resumo, nesta tese são descritos o desenvolvimento e o uso do sideRETRO uma ferramenta computacional robusta e eficiente, designada para identificar e anotar pseudogenes processados não fixados. Por fim, vale destacar que o sideRETRO preenche uma lacuna metodológica e possibilita novas hipóteses e investigações sistemáticas no campo de chamada de variantes estruturais

The methodological and instrumental advances resulting from the Human Genome Project have created the necessary framework to the emergence of Next Generation DNA sequencing technologies, which are characterized by a reduced cost, low operational demand and the generation of a large volume of data per experiment. Concomitantly with this, the increase in computational processing power has driven the development of large-scale genetic analyses, which allowed us to study individualized genomic traits little or never explored before. Among these characteristics, those related to structural variations in genomes have received much attention. Processed pseudogenes, or retrocopies, are structural variations caused by the duplication of coding genes through the transposition of their mature messenger RNA by the LINE-1 enzymatic machinery. Retrocopies can be fixed (i.e., present in all genomes of a given species and included into the assembly of the reference genome) or unfixed, being polymorphic, germinal or somatic. However, knowledge about unfixed retrocopies is still limited due to the lack of bioinformatics tools dedicated to their identification and annotation in DNA sequencing data. Therefore, this work presents sideRETRO a computer program specialized in the detection of processed pseudogenes absent from the reference genome, but present in whole genome and exome sequencing data from other individuals. In addition to pointing out the presence of unfixed retrocopies, sideRETRO is able to annotate several other characteristics related to these events, such as: the genomic coordinate of the processed pseudogene insetion, which constitutes the chromosome, the insertion point and the DNA strand (leader or retard); the genomic context of the event (exonic, intronic or intergenic); genotyping (present or absent) and haplotyping (homozygous or heterozygous). To certify the sideRETRO efficiency, it was run on simulated data and on real data experimentally validated by an independent group. Therefore, in summary, this thesis describes the development and use of sideRETRO a robust and efficient computational tool, designed to identify and annotate unfixed processed pseudogenes. Finally, it is worth noting that sideRETRO fills a methodological gap and allows new hypotheses and systematic investigations in the field of structural variant calling

Exploration of biomarkers in osteoarthritis based on bioinformatics.

ABSTRACT: Osteoarthritis (OA) seriously affects human health and brings a heavy social burden. This study aimed to identify new biomarkers involved in OA. Differential expression analysis and gene set enrichment analysis were performed on the microarray data set of OA. Identify key genes from immune-related DEGs and verify their expression in the validation set. CIBERSORT was used to analyze the infiltration of immune cells. The correlation between key genes and immune cells were conducted. A total of 1779 DEGs were identified in GSE82107. Gene set enrichment analysis results of top 4 for hallmark revealed the enrichment of DEGs were associated with genes in "HALLMARK_TNFA_SIGNALING_VIA_NFKB", "HALLMARK_EPITHELIAL_MESENCHYMAL_TRANSITION", "HALLMARK_INFLAMMATORY_RESPONSE" and "HALLMARK_HYPOXIA". A total of 108 immune-related DEGs were identified from the overlap between 2498 immune-related genes and 1779 DEGs. The expression of top 6 immune-related DEGs including ADIPOQ, FABP4, FOS, IGLC1, IGLV1-44 and leptin were measured in the validation set, the results shown that IGLC1 and IGLV1-44 might play a key role in the synovial membrane of OA. A total of 8 kinds of cells including B cells memory, Plasma cells, T cells CD4 memory resting, T cells gamma delta, natural killer cells activated, macrophages M0, Mast cells resting and Mast cells activated have significant differences in infiltration between the OA group and the control group. Besides, the expressions of IGLC1 and IGLV1-44 are highly correlated. Our results indicated that IGLC1 and IGLV1-44 may play the role of immune-related biomarkers in OA.

High-Throughput Sequencing to Detect DNA-RNA Changes.

The advent of deep sequencing technologies has greatly improved the study of complex eukaryotic genomes and transcriptomes, allowing the investigation of posttranscriptional molecular mechanisms as alternative splicing and RNA editing at unprecedented throughput and resolution. The most prevalent type of RNA editing in higher eukaryotes is the deamination of adenosine to inosine (A-to-I) in double-stranded RNAs. Depending on the RNA type or the RNA region involved, A-to-I RNA editing contributes to the transcriptome and proteome diversity.Hereafter, we present an easy and reproducible computational protocol for the identification of candidate RNA editing sites in humans using deep transcriptome (RNA-Seq) and genome (DNA-Seq) sequencing.

Bioinformatics Pipeline for Human Papillomavirus Short Read Genomic Sequences Classification Using Support Vector Machine.

We recently developed a test based on the Agilent SureSelect target enrichment system capturing genomic fragments from 191 human papillomaviruses (HPV) types for Illumina sequencing. This enriched whole genome sequencing (eWGS) assay provides an approach to identify all HPV types in a sample. Here we present a machine learning algorithm that calls HPV types based on the eWGS output. The algorithm based on the support vector machine (SVM) technique was trained on eWGS data from 122 control samples with known HPV types. The new algorithm demonstrated good performance in HPV type detection for designed samples with 25 or greater HPV plasmid copies per sample. We compared the results of HPV typing made by the new algorithm for 261 residual epidemiologic samples with the results of the typing delivered by the standard HPV Linear Array (LA). The agreement between methods (97.4%) was substantial (kappa= 0.783). However, the new algorithm identified additionally 428 instances of HPV types not detectable by the LA assay by design. Overall, we have demonstrated that the bioinformatics pipeline is an accurate tool for calling HPV types by analyzing data generated by eWGS processing of DNA fragments extracted from control and epidemiological samples.

Two mutations in the axonemal dynein heavy chain gene 5 in a Chinese asthenozoospermia patient: A case report.

INTRODUCTION: As one of the most common causes of male infertility, asthenozoospermia mainly shows low sperm motility, accounting for 81.84% of male infertility patients. Recently, there has been a notable increase for relationship between genetic testing and asthenozoospermia. In this report, we design to provide clues to prove relationship between dynein heavy chain gene 5 (DNAH5) gene alterations and asthenozoospermia. This also provides a reference for patients to choose a reasonable treatment plan or genetic counseling to assist reproductive reproduction. PATIENTS CONCERN: In the present study, we screened 143 patients with asthenozoospermia for variants in DNAH5 gene. We used high-throughput targeted gene sequencing technology and the data were assessed by bioinformatics analysis. DIAGNOSIS: We found 1 of 143 asthenozoospermia patients was detected as carrying DNAH5 compound heterozygous variants (c.3502G>A and c.2578-11_2578-7del). OUTCOMES: The variation c.2578-11_2578-7del was predicted in silico to not affect the splicing by HSF3. The variation c.3502G > A (p.E1168K) may cause disease by Mutationtaster software. They may contribute to a risk of male infertility in Chinese patients. CONCLUSIONS: We discussed the possible association between mutations in DNAH5 and asthenospermia for the first time in Chinese people. If confirmed in larger samples and different races, this result was meaningful for a better diagnosis of asthenospermia patients.

Systems Wide Analysis of CCM Signaling Complex Alterations in CCM-Deficient Models Using Omics Approaches.

Omics research has garnered popularity recently to integrate in-depth analysis of alterations at the molecular level to elucidate observable phenotypes resulting from knockdown/knockout models. Genomics, performed through RNA-seq, allows the user to evaluate alterations at the transcription level, oftentimes more sensitive than other types of analysis, especially when attempting to understand lack of observation of an expected phenotype. Proteomics facilitates an understanding of mechanisms being altered at the translational level allowing for an understanding of multiple layers of regulation occurring, elucidating discrepancies between what is seen at the RNA level compared to what is translated to a functional protein. Here we describe the methods currently being used to evaluate CCM-deficient strains in human brain microvascular endothelial cells (HBMVEC), zebrafish embryos as well as in vivo mouse model to evaluate impacts on various signaling cascades resulting from deficiencies in KRIT1 (CCM1), MGC4607 (CCM2), and PDCD10 (CCM3). The integration of data from genomics and proteomics analysis allows for the composition of interactomes, elucidating systems wide impacts resulting from disruption of the CCM signaling complex (CSC).

Integrated miRNA-mRNA network revealing the key molecular characteristics of ossification of the posterior longitudinal ligament.

BACKGROUND: Ossification of the posterior longitudinal ligament (OPLL) refers to an ectopic ossification disease originating from the posterior longitudinal ligament of the spine. Pressing on the spinal cord or nerve roots can cause limb sensory and motor disorders, significantly reducing the patient's quality of life. At present, the pathogenesis of OPLL is still unclear. The purpose of this study is to integrate microRNA (miRNA)-mRNA biological information data to further analyze the important molecules in the pathogenesis of OPLL, so as to provide targets for future OPLL molecular therapy. METHODS: miRNA and mRNA expression profiles of GSE69787 were downloaded from Gene Expression Omnibus database and analyzed by edge R package. Funrich software was used to predict the target genes and transcription factors of de-miRNA. Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis of differentially expressed genes (DEGs) were carried out based on CLUEGO plug-in in Cytoscape. Using data collected from a search tool for the retrieval of interacting genes online database, a protein-protein interaction (PPI) network was constructed using Cytoscape. The hub gene selection and module analysis of PPI network were carried out by cytoHubba and molecular complex detection, plug-ins of Cytoscape software respectively. RESULTS: A total of 346 genes, including 247 up-regulated genes and 99 down-regulated genes were selected as DEGs. SP1 was identified as an upstream transcription factor of de-miRNAs. Notably, gene ontology enrichment analysis shows that up- and down-regulated DEGs are mainly involved in BP, such as skeletal structure morphogenesis, skeletal system development, and animal organ morphogenesis. Kyoto Encyclopedia of Genes and Genomes enrichment analysis indicated that only WNT signaling pathway was associated with osteogenic differentiation. Lymphoid enhancer binding factor 1 and wingless-type MMTV integration site family member 2 Wingless-Type MMTV Integration site family member 2 were identified as hub genes, miR-520d-3p, miR-4782-3p, miR-6766-3p, and miR-199b-5p were identified as key miRNAs. In addition, 2 important network modules were obtained from PPI network. CONCLUSIONS: In this study, we established a potential miRNA-mRNA regulatory network associated with OPLL, revealing the key molecular mechanism of OPLL and providing targets for future treatment or prevent its occurrence.

GenomeScope 2.0 and Smudgeplot for reference-free profiling of polyploid genomes.

An important assessment prior to genome assembly and related analyses is genome profiling, where the k-mer frequencies within raw sequencing reads are analyzed to estimate major genome characteristics such as size, heterozygosity, and repetitiveness. Here we introduce GenomeScope 2.0 (https://github.com/tbenavi1/genomescope2.0), which applies combinatorial theory to establish a detailed mathematical model of how k-mer frequencies are distributed in heterozygous and polyploid genomes. We describe and evaluate a practical implementation of the polyploid-aware mixture model that quickly and accurately infers genome properties across thousands of simulated and several real datasets spanning a broad range of complexity. We also present a method called Smudgeplot (https://github.com/KamilSJaron/smudgeplot) to visualize and estimate the ploidy and genome structure of a genome by analyzing heterozygous k-mer pairs. We successfully apply the approach to systems of known variable ploidy levels in the Meloidogyne genus and the extreme case of octoploid Fragaria × ananassa.

Identifying multi-hit carcinogenic gene combinations: Scaling up a weighted set cover algorithm using compressed binary matrix representation on a GPU.

Despite decades of research, effective treatments for most cancers remain elusive. One reason is that different instances of cancer result from different combinations of multiple genetic mutations (hits). Therefore, treatments that may be effective in some cases are not effective in others. We previously developed an algorithm for identifying combinations of carcinogenic genes with mutations (multi-hit combinations), which could suggest a likely cause for individual instances of cancer. Most cancers are estimated to require three or more hits. However, the computational complexity of the algorithm scales exponentially with the number of hits, making it impractical for identifying combinations of more than two hits. To identify combinations of greater than two hits, we used a compressed binary matrix representation, and optimized the algorithm for parallel execution on an NVIDIA V100 graphics processing unit (GPU). With these enhancements, the optimized GPU implementation was on average an estimated 12,144 times faster than the original integer matrix based CPU implementation, for the 3-hit algorithm, allowing us to identify 3-hit combinations. The 3-hit combinations identified using a training set were able to differentiate between tumor and normal samples in a separate test set with 90% overall sensitivity and 93% overall specificity. We illustrate how the distribution of mutations in tumor and normal samples in the multi-hit gene combinations can suggest potential driver mutations for further investigation. With experimental validation, these combinations may provide insight into the etiology of cancer and a rational basis for targeted combination therapy.

Usando a imunologia de sistemas para entender os mecanismos moleculares de doenças e vacinas / Using systems immunology to understand the molecular mechanisms of diseases and vaccines

Nas últimas décadas, dados relacionados com a saúde humana, desde informações clínicas e epidemiológicas até imagens médicas e experimentos ômicos, foram gerados e acumulados em uma quantidade sem precedentes na história. Um campo novo de pesquisa chamado "Imunologia de Sistemas" emergiu para tentar integrar, analisar, interpretar e predizer os mecanismos moleculares de doenças e vacinas. Esta tese mostra diversas aplicações da Imunologia de Sistemas no estudo de arboviroses, vacina da gripe, câncer, tuberculose, pneumonia, artrite, dentre outros. Também mostra o desenvolvimento de ferramentas computacionais amigáveis que permitem com que qualquer cientista, sem conhecimento prévio de bioinformática, possa realizar análises de Imunologia de Sistemas. Os achados das análises forneceram novas hipóteses e insights que, ao serem testados e validados experimentalmente, melhoram nosso entendimento sobre os processos imunológicos por trás da vacinação e de doenças humanas

GEDS: A Gene Expression Display Server for mRNAs, miRNAs and Proteins.

High-throughput technologies generate a tremendous amount of expression data on mRNA, miRNA and protein levels. Mining and visualizing the large amount of expression data requires sophisticated computational skills. An easy to use and user-friendly web-server for the visualization of gene expression profiles could greatly facilitate data exploration and hypothesis generation for biologists. Here, we curated and normalized the gene expression data on mRNA, miRNA and protein levels in 23315, 9009 and 9244 samples, respectively, from 40 tissues (The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GETx)) and 1594 cell lines (Cancer Cell Line Encyclopedia (CCLE) and MD Anderson Cell Lines Project (MCLP)). Then, we constructed the Gene Expression Display Server (GEDS), a web-based tool for quantification, comparison and visualization of gene expression data. GEDS integrates multiscale expression data and provides multiple types of figures and tables to satisfy several kinds of user requirements. The comprehensive expression profiles plotted in the one-stop GEDS platform greatly facilitate experimental biologists utilizing big data for better experimental design and analysis. GEDS is freely available on http://bioinfo.life.hust.edu.cn/web/GEDS/.

QuBiT: a quantitative tool for analyzing epithelial tubes reveals unexpected patterns of organization in the Drosophila trachea.

Biological tubes are essential for animal survival, and their functions are dependent on tube shape. Analyzing the contributions of cell shape and organization to the morphogenesis of small tubes has been hampered by the limitations of existing programs in quantifying cell geometry on highly curved tubular surfaces and calculating tube-specific parameters. We therefore developed QuBiT (Quantitative Tool for Biological Tubes) and used it to analyze morphogenesis of the embryonic Drosophila trachea (airway). In the main tube, we find previously unknown anterior-to-posterior (A-P) gradients of cell apical orientation and aspect ratio, and periodicity in the organization of apical cell surfaces. Inferred cell intercalation during development dampens an A-P gradient of the number of cells per cross-section of the tube, but does not change the patterns of cell connectivity. Computationally 'unrolling' the apical surface of wild-type trachea and the hindgut reveals previously unrecognized spatial patterns of the apical marker Uninflatable and a non-redundant role for the Na+/K+ ATPase in apical marker organization. These unexpected findings demonstrate the importance of a computational tool for analyzing small diameter biological tubes.

MicroRNA-448 inhibits the regeneration of spinal cord injury through PI3K/AKT/Bcl-2 axis.

OBJECTIVE: This study aims to elucidate the potential role of microRNA-448 in the recovery of spinal cord injury (SCI), and to explore the underlying mechanism. MATERIALS AND METHODS: MicroRNA-448 expression was determined by microarray and the established SCI model in mice. The target gene of microRNA-448 was predicted using bioinformatics. The functional binding of the target gene to microRNA-448 was verified by Dual-Luciferase reporter gene assay. The regulatory effects of microRNA-448 and Bcl-2 on apoptosis, motor neuron number and grip strength were evaluated. After injection of microRNA-448 mimics, microRNA-448 inhibitor or Bcl-2 siRNA in mice, expression levels of PI3K/AKT and Caspase3 were detected by quantitative Real Time-Polymerase Chain Reaction (qRT-PCR) and Western blot. RESULTS: Grip strength of SCI mice significantly decreased compared with mice in the sham group. The microRNA-448 expression gradually increased with the progression of SCI, whereas the Bcl-2 expression decreased. Dual-Luciferase reporter gene assay showed the binding condition between microRNA-448 and Bcl-2. Furthermore, the Bcl-2 expression was negatively regulated by microRNA-448 at both mRNA and protein levels. The injection of microRNA-448 inhibitor into the injured spinal cord of SCI mice significantly upregulated the expressions of p-PI3K, p-AKT and Caspase3, as well as motor neuron regeneration and grip strength. However, the promotive effects of microRNA-448 inhibitor were blocked by Bcl-2 siRNA transfection. CONCLUSIONS: MicroRNA-448 is upregulated after SCI, which may be involved in the regenerative process of spinal motor nerves by regulating PI3K/AKT/Bcl-2 axis.

Deep convolutional neural networks for accurate somatic mutation detection.

Accurate detection of somatic mutations is still a challenge in cancer analysis. Here we present NeuSomatic, the first convolutional neural network approach for somatic mutation detection, which significantly outperforms previous methods on different sequencing platforms, sequencing strategies, and tumor purities. NeuSomatic summarizes sequence alignments into small matrices and incorporates more than a hundred features to capture mutation signals effectively. It can be used universally as a stand-alone somatic mutation detection method or with an ensemble of existing methods to achieve the highest accuracy.

Methods for Annotation and Validation of Circular RNAs from RNAseq Data.

Circular RNAs are an emerging class of transcript isoforms created by unique back splicing of exons to form a closed covalent circular structure. While initially considered as product of aberrant splicing, recent evidence suggests unique functions and conservation across evolution. While circular RNAs could be largely attributed to have little or no potential to encode for proteins, recent evidence points to at least a small subset of circular RNAs which encode for peptides. Circular RNAs are also increasingly shown to be biomarkers for a number of diseases including neurological disorders and cancer. The advent of deep sequencing has enabled large-scale identification of circular RNAs in human and other genomes. A number of computational approaches have come up in recent years to query circular RNAs on a genome-wide scale from RNA-seq data. In this chapter, we describe the application and methodology of identifying circular RNAs using three popular computational tools: FindCirc, Segemehl, and CIRI along with approaches for experimental validation of the unique splice junctions.

Integration of miRNA and mRNA Expression Data for Understanding Etiology of Gynecologic Cancers.

Dysregulation of miRNA-mRNA regulatory networks is very common phenomenon in any diseases including cancer. Altered expression of biomarkers leads to these gynecologic cancers. Therefore, understanding the underlying biological mechanisms may help in developing a robust diagnostic as well as a prognostic tool. It has been demonstrated in various studies that the pathways associated with gynecologic cancer have dysregulated miRNA as well as mRNA expression. Identification of miRNA-mRNA regulatory modules may help in understanding the mechanism of altered gynecologic cancer pathways. In this regard, an existing robust mutual information-based Maximum-Relevance Maximum-Significance algorithm has been used for identification of miRNA-mRNA regulatory modules in gynecologic cancer. A set of miRNA-mRNA modules are identified first than their association with gynecologic cancer are studied exhaustively. The effectiveness of the proposed approach is compared with the existing methods. The proposed approach is found to generate more robust integrated networks of miRNA-mRNA in gynecologic cancer.

Statistical Methods for Identifying Biomarkers from miRNA Profiles of Cancers.

Biomarkers play important roles in early diagnosis and treatment plan for cancer patients and the importance is growing. With advances in high-throughput molecular profiling technology for various types of molecules such as DNA, RNA, proteins, or metabolites, it is now possible to perform massive profiling analysis that allows accelerating discovery of novel biomolecules. Because no single marker is sufficiently accurate for clinical use, the cancer biomarker is developed in the form of multiple biomarker panels. No single marker is sufficiently accurate for clinical use, and thus cancer biomarkers are developed in the form of multiple biomarker panels. Of various types of molecular biomarkers, microRNA (miRNA) has emerged as a class of promising cancer biomarker recently. MiRNAs are small noncoding RNAs that regulate gene expression. The chapter overviews the process of identification of biomarker panels from miRNA profiles focusing on statistical methods. Introduction to molecular cancer biomarkers is touched first. From sample design to miRNA profiling process is reviewed in the method section.Statistical methods for biomarker development are introduced according to three typical purposes of molecular biomarkers: tumor subtype classification, early detection, and prediction of treatment response or prognosis of patients. Example codes for R program are provided as well for selected methods.